• Korea Journal of Hospital Management
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• v.18 no.2
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• pp.81-103
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• 2013

This study is to research cost accounting practice and to analyze propriety of patients' medical payment in artificiality kidney center. The researched cost datum of the year 2012 are as follows. - Hemodialysis medical treatment was reimbursed as much as 158,001 won in case of health insured patients, but payed-off as much as 135,810 won. - The average figure of the total hospitals and clinic center is 1,603,303 won, and one time cost of hemodialysis treatment is 154,487 won. Optimal treatment pay are suggested as follows. First, Regardless of the notified classification from MOHW(Ministry of Health and Welfare), 136,000 won of fixed price payment classification needs to be reclassified by patients, severity and tobe rearranged by fixed price payment system of hospitals. Second, Fixed payment code notified by the Ministry of Health and Welfare is recommended to be simplifies and to reflect according to contents of the medical treatment rendered to patients. Third, Establishment of artificial kidney center has to be risk managed because of its huge investment. Fourth, Cost analysis model has to be maintained as basis together with appropriate application of conversion index model mixed with SGR model.

• Journal of Korean Academy of Nursing Administration
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• v.14 no.2
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• pp.118-130
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• 2008

Purpose: The purpose of this study was to estimate of home-visiting nursing costs for low-income elderly with chronic disease in a metropolitan city using the severity classification and ABC(active-based costing). Methods: First, the HHC activity pool was established. The performance time of each nursing activity were estimated. Second, nursing resources(labor costs, operating costs, and traffic expenses) were analyzed and nursing cost per minute was calculated. And then the cost of each activity was estimated. Third, 202 visiting cases were classified into three group by their severity. And then nursing cost per visit according to their severity was estimated. Results: 59 nursing activities were included in HHC activity pool. The average working time of 59 nursing activity was 6.7minutes and nursing cost per minute was 489 won. According severity, nursing cost per visit were in class I, 54,296 (won), class II 83,124(won), and class III 93,455(won).

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.10a
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• pp.157-162
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• 2004

Recently, Life Cycle Cost (LCC) for civil infrastructures, such as pavements, bridges, and dams, has been emphasized. However there are few cost models for road tunnel especially for maintenance phase. The road network is composed of highways, bridges, and road tunnels. Thus it is as important as for road tunnels to keep safe for traffic. The maintenance strategies for road tunnels can be achieved based on the minimization of LCC in maintenance phase. For this purpose, in this paper, cost model and cost classification for road tunnel in maintenance phase are suggested.

• Journal of Korea Society of Industrial Information Systems
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• v.6 no.2
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• pp.1-6
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• 2001

This paper proposes a pattern classification method of interval vectors by interval neural networks. The proposed method can be applied to pattern classification where attribute values of each sample are given as interval numbers. First, an architecture of interval neural networks is proposed for dealing with interval input vectors. Next, a learning algorithm is derived from the cost function. a cost function is defined using the interval output from the interval neural network and the corresponding target output. Last, using numerical examples, the proposed approach is illustrated and compared with other approach based on the standard back-propagation neural networks.

• Journal of Power Electronics
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• v.15 no.1
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• pp.256-267
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• 2015

Grid-connected transformerless photovoltaic (PV) inverters (TPVIs) are increasingly dominating the market due to their higher efficiency, lower cost, lighter weight, and reduced size when compared to their transformer based counterparts. However, due to the lack of galvanic isolation in the low voltage grid interconnections of these inverters, the PV systems become vulnerable to leakage currents flowing through the grounded star point of the distribution transformer, the earth, and the distributed parasitic capacitance of the PV modules. These leakage currents are prohibitive, since they constitute an issue for safety, reliability, protection coordination, electromagnetic compatibility, and module lifetime. This paper investigates a wide range of multi-kW range power rating TPVI topologies and classifies them in terms of their leakage current attributes. This systematic classification places most topologies under a small number of classes with basic leakage current attributes. Thus, understanding and evaluating these topologies becomes an easy task. In addition, based on these observations, new topologies with reduced leakage current characteristics are proposed in this paper. Furthermore, the important efficiency and cost determining characteristics of converters are studied to allow design engineers to include cost and efficiency as deciding factors in selecting a converter topology for PV applications.

• Journal of the Korea Society of Computer and Information
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• v.14 no.3
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• pp.209-216
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• 2009

The accurate estimation of software development cost is important to a successful development in software engineering. This paper presents a software cost estimation method using a support vector machine. Support vector machine is one of the efficient techniques for classification, and it is the classification method of input data based on Maximum-Margin Hyperplane. But SVM has the problem of the selection of optimal parameters, because it is dependent on user's parameters. This paper selects optimized SVM parameters using advanced method, and estimates software development cost. The proposed approach outperform some recent results reported in the literature.

• Genomics & Informatics
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• v.1 no.2
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• pp.80-86
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• 2003

Human Papillomavirus (HPV) infection is known as the main factor for cervical cancer which is a leading cause of cancer deaths in women worldwide. Because there are more than 100 types in HPV, it is critical to discriminate the HPVs related with cervical cancer from those not related with it. In this paper, the risk type of HPVs using their textual explanation. The important issue in this problem is to distinguish false negatives from false positives. That is, we must find high-risk HPVs as many as possible though we may miss some low-risk HPVs. For this purpose, the AdaCost, a cost-sensitive learner is adopted to consider different costs between training examples. The experimental results on the HPV sequence database show that the consideration of costs gives higher performance. The improvement in F-score is higher than that of the accuracy, which implies that the number of high-risk HPVs found is increased.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.4
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• pp.33-40
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• 2016

Previous works for detecting arrhythmia have mostly used nonlinear method to increase classification accuracy. Most methods require accurate detection of ECG signal, higher computational cost and larger processing time. But it is difficult to analyze the ECG signal because of various noise types. Also in the healthcare system based IOT that must continuously monitor people's situation, it is necessary to process ECG signal in realtime. Therefore it is necessary to design efficient algorithm that classifies different arrhythmia in realtime and decreases computational cost by extrating minimal feature. In this paper, we propose R wave detection considering complexity and arrhythmia classification based on binary coding. For this purpose, we detected R wave through SOM and then RR interval from noise-free ECG signal through the preprocessing method. Also, we classified arrhythmia in realtime by converting threshold variability of feature to binary code. R wave detection and PVC, PAC, Normal classification is evaluated by using 39 record of MIT-BIH arrhythmia database. The achieved scores indicate the average of 99.41%, 97.18%, 94.14%, 99.83% in R wave, PVC, PAC, Normal.

• Korean Journal of Computational Design and Engineering
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• v.12 no.5
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• pp.382-394
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• 2007

Nowadays, manufacturing industries undergo constantly growing pressures for global competitions, and they must shorten time and cost in product development and production to response varied customers' requirements. Digital virtual manufacturing is a technology that can facilitate effective product development and agile production by using digital models representing the physical and logical schema and the behavior of real manufacturing systems including products, processes, manufacturing resources and plants. For successful applications of this technology, a digital virtual factory as a well-designed and integrated environment is essential. In this paper, we developed a new classification and coding system for effective managements of digital virtual factory objects, and implement a supporting application to verify and apply it. Furthermore, a digital virtual factory layout management system based on the classification and coding system has developed using XML, Visual Basic.NET and FactoryCAD. By some case studies for automotive general assembly shops of a Korean automotive company, efficient management of factory objects and reduction of time and cost in digital virtual factory constructions are possible.

• Smart Structures and Systems
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• v.13 no.5
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• pp.849-868
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• 2014

An indirect approach is explored for structural health bridge monitoring allowing for wide, yet cost-effective, bridge stock coverage. The detection capability of the approach is tested in a laboratory setting for three different reversible proxy types of damage scenarios: changes in the support conditions (rotational restraint), additional damping, and an added mass at the midspan. A set of frequency features is used in conjunction with a support vector machine classifier on data measured from a passing vehicle at the wheel and suspension levels, and directly from the bridge structure for comparison. For each type of damage, four levels of severity were explored. The results show that for each damage type, the classification accuracy based on data measured from the passing vehicle is, on average, as good as or better than the classification accuracy based on data measured from the bridge. Classification accuracy showed a steady trend for low (1-1.75 m/s) and high vehicle speeds (2-2.75 m/s), with a decrease of about 7% for the latter. These results show promise towards a highly mobile structural health bridge monitoring system for wide and cost-effective bridge stock coverage.